Learning Under Ambiguity
This paper considers learning when the distinction between risk and ambiguity matters. It first describes thought experiments, dynamic variants of those provided by Ellsberg, that highlight a sense in which the Bayesian learning model is extreme-it models agents who are implausibly ambitious about what they can learn in complicated environments. The paper then provides a generalization of the Bayesian model that accommodates the intuitive choices in the thought experiments. In particular, the model allows decision-makers' confidence about the environment to change-along with beliefs-as they learn. A portfolio choice application compares the effect of changes in confidence under ambiguity vs. changes in estimation risk under Bayesian learning. The former is shown to induce a trend towards more stock market participation and investment even when the latter does not. Copyright 2007 The Review of Economic Studies Limited.
Year of publication: |
2007
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Authors: | EPSTEIN, LARRY G. ; SCHNEIDER, MARTIN |
Published in: |
Review of Economic Studies. - Wiley Blackwell, ISSN 0034-6527. - Vol. 74.2007, 4, p. 1275-1303
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Publisher: |
Wiley Blackwell |
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